The present application relates to produce recognition systems, and is particularly directed to a produce color data correction method and an apparatus therefore. The method and apparatus may be embodied in a produce recognition system in a retail checkout environment.
Automated or operator-assisted identification methods for identifying produce items are known. The known methods may use color as the main factor in identifying a produce item. An imaging camera may be used to capture produce color data associated with a produce item placed on a produce weighing scale. The captured produce color data is then processed to either identify the produce item or to display a list and/or stored images of produce items on the list for verification by an operator.
A drawback in using color as a factor in identifying a produce item is that measured color of the produce item varies with changes in illumination color which, in turn, varies with changes in natural light, changes in interior light, and the balance between natural light and interior light. Sunlight, clouds, window effects, and reflections, for examples, may cause changes in natural light. Type of light source, age of the light source, cycle phase (if alternating current) of the light source, and reflections, for examples, may cause changes in interior light. It would be desirable to correct variations in measured color of a produce item due to either variations in natural light or variations in interior light.